A driving premise behind this application is that endometrial cancer is strongly related to excessive exposure to unopposed estrogens. Estrogens drive cell proliferation, and thus the opportunity for the accumulation of random genetic errors that can lead to progression of endometrial cancer. Sulfate conjugation plays an important role in the biotransformation of estrogens. Estrogen sulfotransferases catalyze the conversion of biologically active estrogens to inactive estrogen sulfates, thereby "diverting" these hormones from both receptor mediated and genotoxic pathways leading to carcinogenesis. Estrogen sulfatases, on the other hand, hydrolyze biologically inactive estrogen-sulfate to active estrogens. Glucuronidation, catalyzed by UDP-glucuronosyl transferase enzymes, is another pathway through which estrogens can be metabolized to inactive compounds. These enzymes are expressed in the endometrium and play an important role in the regulation of local estrogenic production. We hypothesize that functional polymorphisms in genes regulating estrogen conjugation are associated with endometrial cancer risk. A comprehensive evaluation of common genetic variation in these genes in relation to endometrial cancer risk has not been conducted. In this application, we will examine associations between putative functional polymorphisms and tagging single nucleotide polymorphisms (SNPs) in SULT1A1, SULT1E1, STS and UGT1A1 with endometrial cancer risk, along with genexgene and genexenvironment interactions with established endometrial cancer risk factors, in two case-control studies nested within two large prospective cohorts: the Multiethnic Cohort (500 cases and 1,000 controls) and the California Teachers Study (400 cases and 800 controls). By combining these studies we will be able to cross-validate and replicate suggestive findings, and have an adequate statistical power to detect modest effects associated with common alleles and to explore genexgene and genexenvironment interactions. Here we will utilize novel high-throughput multiplexing genotyping technology for evaluating many SNPs and apply a rigorous statistical analytic method to account for multiple comparison issue. Finally, our cohorts are unique because they provide an opportunity to study variations in genetic susceptibility to endometrial cancer and environmental risk factors in multiethnic and sometimes underserved populations in the U.S. The discovery of disease alleles would have an important public health implication as it helps identify high-risk women who would benefit the most from prevention measures.